# Inventory Logiq

> Inventory Logiq: An AI-native Inventory Planning team for eCommerce, Not Software


## Posts

- [Inside Our Sample Report: What Inventory Forecasting for D2C Brands Looks Like](https://inventorylogiq.com/inventory-forecasting-d2c-brands-sample-report/): Most founders doing $1M–$5M in D2C revenue already know their inventory is imprecise. They know because there’s a Slack message every few months about something running out. They know because there’s always one SKU sitting at 180 days of cover while something else goes critical. They know because the spreadsheet that “works” depends entirely on the one person who built it still being around. What they usually don’t have is a clear picture of what good actually looks like – what inventory forecasting for D2C brands looks like when someone is consistently applying judgement to it, week in week out. […]
- [What AI-Native Inventory Planning Actually Means(And Why Most Tools Don't Qualify)](https://inventorylogiq.com/ai-native-inventory-planning/): Every inventory software vendor has added “AI” to their homepage in the last 18 months. AI-powered forecasting. AI-driven reorder suggestions. AI insights dashboards. If you’re a D2C founder trying to figure out what’s actually different, you’re not confused because you don’t understand the technology. You’re confused because most of what’s being sold as AI-native inventory planning isn’t. What follows isn’t an opinion piece. It’s a walkthrough of what the models actually do differently – with demand data, fit curves, and accuracy numbers – so you can evaluate any vendor or approach with the same lens we use internally. The Label […]
- [Why Your Inventory Forecasting Is Failing (And It's Not Your Team's Fault)](https://inventorylogiq.com/inventory-forecasting-d2c-failing/): Most D2C brands run one forecasting model across every SKU. That single assumption is costing you stockouts, dead stock and emergency POs. Here's why — and what the fix looks like.

## Pages

- [](https://inventorylogiq.com/stocky-alternative/): Stocky Alternative — Inventory Logiq Stocky Alternative  /  Forecasting & Purchase Orders Stocky is shutting down.Switch to a forecasting engine that does it better. Inventory Logiq is a Stocky alternative built for Shopify brands that need better demand forecasting and purchase order planning after Stocky’s shutdown. Contact Us See how we compare → Holdout validation per SKU Multiple models compete per SKU POs from forecasts Decisions, not dashboards Stocky shutdown timeline ✓ Already done Forecasting & Transfers removed July 7, 2025 — Min/max settings and inventory transfers disabled. ✓ Already done Delisted from App Store February 2, 2026 — No […]
- [Contact Us](https://inventorylogiq.com/contact-us/): Contact Us
- [Thank You](https://inventorylogiq.com/thank-you/): We have received your request and will be in touch within one business day. In the meantime, if you have any questions you can reach us at hello@inventorylogiq.com
- [Resources](https://inventorylogiq.com/resources/): Resources March 7, 2026 March 7, 2026 March 5, 2026 March 5, 2026 March 5, 2026 March 5, 2026
- [Inventorylogiq](https://inventorylogiq.com/): Inventory Logiq – AI Inventory Planning Resources Pricing How it works Contact Request Demo Resources Pricing How it works Contact Request Demo Backed by Combinator Battle-tested across 400+ D2C brands Your external inventory planning team, powered by a competitive AI forecasting engine Our forecasting engine combines transformer-based AI models with classical machine learning, validated per SKU, to produce three decisions: reorder, overstock, and redistribute. Not DIY dashboards. You get a world-class planning team working with you each cycle, on a simple monthly retainer. Request a planning sample See how the engine works Observed signals Sales history Inventory levels Stockouts / […]
- [How It Works](https://inventorylogiq.com/how-it-works/): How It Works – Inventory Logiq Resources Pricing How it works Contact Request Demo Resources Pricing How it works Contact Request Demo How Inventory Logiq works There is no single best forecasting model. Demand shapes differ by SKU. We run a competition, validate on actuals, and force outputs into decisions you can execute Request Demo Holdout validation Models tested on unseen data before selection Bias tracked Systematic over/under-forecasting measured per model Stability scored Forecast consistency across re-estimation cycles A tournament of models per SKU •Multiple candidate models run per SKU •Winner selected on holdout error + stability + bias •Winner […]

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- [Agent (MCP protocol)](websites-agents.hostinger.com/inventorylogiq.com/mcp)

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